Most Cited ICLR "vision-language context sparsification" Papers
6,124 papers found • Page 23 of 31
Conference
A Multi-Level Framework for Accelerating Training Transformer Models
Longwei Zou, Han Zhang, Yangdong Deng
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu et al.
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
Jingchu Gai, Yiheng Du, Bohang Zhang et al.
The Labyrinth of Links: Navigating the Associative Maze of Multi-modal LLMs
HONG LI, Nanxi Li, Yuanjie Chen et al.
MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
Carlo Abate, Filippo Maria Bianchi
Global Convergence in Neural ODEs: Impact of Activation Functions
Tianxiang Gao, Siyuan Sun, Hailiang Liu et al.
Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture
Sajad Movahedi, Antonio Orvieto, Seyed-Mohsen Moosavi-Dezfooli
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann et al.
Learning the Complexity of Weakly Noisy Quantum States
Yusen Wu, Bujiao Wu, Yanqi Song et al.
Decodable and Sample Invariant Continuous Object Encoder
Dehao Yuan, Furong Huang, Cornelia Fermuller et al.
ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
Yuanchen Wu, Junlong Du, Ke Yan et al.
DECO: Unleashing the Potential of ConvNets for Query-based Detection and Segmentation
Xinghao Chen, Siwei Li, Yijing Yang et al.
Expected Return Symmetries
Darius Muglich, Johannes Forkel, Elise van der Pol et al.
CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning
Fanxu Meng, Muhan Zhang
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit, Liangze Jiang, Andrei Atanov et al.
Enhancing Graph Of Thought: Enhancing Prompts with LLM Rationales and Dynamic Temperature Control
Sunguk Shin, Youngjoon Kim
Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators
Pratyush Maini, Hritik Bansal
Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields
Brandon Zhao, Aviad Levis, Liam Connor et al.
The Effectiveness of Random Forgetting for Robust Generalization
Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe Arani
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
Angela Zhou, Christoph Kern, Michael Kim
Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
Chen Xu, Yuxin Li, Wenjie Wang et al.
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang et al.
DUALFormer: Dual Graph Transformer
Zhuo Jiaming, Yuwei Liu, Yintong Lu et al.
Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
Ruohong Liu, Yuxin Pan, Linjie Xu et al.
Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
Hengzhuang Li, Teng Zhang
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
Rana Muhammad Shahroz Khan, Pingzhi Li, Sukwon Yun et al.
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
Yongyi Su, Yushu Li, Nanqing Liu et al.
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Jasper Dekoninck, Maximilian Baader, Martin Vechev
PEARL: Towards Permutation-Resilient LLMs
Liang CHEN, Li Shen, Yang Deng et al.
Let the Code LLM Edit Itself When You Edit the Code
Zhenyu He, Jun Zhang, Shengjie Luo et al.
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
Chengming Hu, Haolun Wu, Xuan Li et al.
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
Thomas Stegmüller, Tim Lebailly, Nikola Đukić et al.
Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building
Jaedong Hwang, Zhang-Wei Hong, Eric Chen et al.
Towards Automated Knowledge Integration From Human-Interpretable Representations
Katarzyna Kobalczyk, Mihaela van der Schaar
Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
RETSim: Resilient and Efficient Text Similarity
Marina Zhang, Owen Vallis, Aysegul Bumin et al.
Hyperbolic Genome Embeddings
Raiyan Khan, Philippe Chlenski, Itsik Pe'er
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations
Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter et al.
ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials
Pin Chen, Zexin Xu, Qing Mo et al.
From Promise to Practice: Realizing High-performance Decentralized Training
Zesen Wang, Jiaojiao Zhang, Xuyang Wu et al.
Towards Poisoning Fair Representations
Tianci Liu, Haoyu Wang, Feijie Wu et al.
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
Haoran Xu, Shuozhe Li, Harshit Sikchi et al.
Large Language Models can Become Strong Self-Detoxifiers
Ching-Yun Ko, Pin-Yu Chen, Payel Das et al.
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Caleb Chuck, Fan Feng, Carl Qi et al.
Agent-to-Sim: Learning Interactive Behavior Models from Casual Longitudinal Videos
Gengshan Yang, Andrea Bajcsy, Shunsuke Saito et al.
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Pengwei Tang, Xiaolin Hu, Yong Liu
Task Descriptors Help Transformers Learn Linear Models In-Context
Ruomin Huang, Rong Ge
Select to Perfect: Imitating desired behavior from large multi-agent data
Tim Franzmeyer, Edith Elkind, Philip Torr et al.
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux, Max Zimmer, Sebastian Pokutta
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Huimin Xu, Feng-Lin Li et al.
Robust Model-Based Optimization for Challenging Fitness Landscapes
Saba Ghaffari, Ehsan Saleh, Alex Schwing et al.
FIG: Flow with Interpolant Guidance for Linear Inverse Problems
Yici Yan, Yichi Zhang, XIANGMING MENG et al.
ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift
Hwanwoo Kim, Xin Zhang, Jiwei Zhao et al.
GMValuator: Similarity-based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu et al.
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
YUJIE MO, Runpeng Yu, Xiaofeng Zhu et al.
Robustness Inspired Graph Backdoor Defense
Zhiwei Zhang, Minhua Lin, Junjie Xu et al.
AutoG: Towards automatic graph construction from tabular data
Zhikai Chen, Han Xie, Jian Zhang et al.
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee et al.
Enhancing Learning with Label Differential Privacy by Vector Approximation
Puning Zhao, Jiafei Wu, Zhe Liu et al.
Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning
Hanlin Yang, Jian Yao, Weiming Liu et al.
Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams et al.
Tailoring Mixup to Data for Calibration
Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
Jungtaek Kim, Jeongbeen Yoon, Minsu Cho
Maximum Entropy Model Correction in Reinforcement Learning
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh et al.
WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning
Kai Jungel, Dario Paccagnan, Axel Parmentier et al.
MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations
Shaochen Zhong, Yifan (Louie) Lu, Lize Shao et al.
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models
Yongjin Yang, Sihyeon Kim, Hojung Jung et al.
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering
Jiaxin Lu, Zetian Jiang, Tianzhe Wang et al.
Perceptual Scales Predicted by Fisher Information Metrics
Jonathan Vacher, Pascal Mamassian
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
Saket Tiwari, Omer Gottesman, George D Konidaris
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee, Seungju Cho, Changick Kim
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
Yangming Li, Boris van Breugel, Mihaela van der Schaar
A Truncated Newton Method for Optimal Transport
Mete Kemertas, Amir-massoud Farahmand, Allan Jepson
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Futa Waseda, Ching-Chun Chang, Isao Echizen
Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning
Shumao Zhai, Ning Ge
Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe et al.
NL-Eye: Abductive NLI For Images
Mor Ventura, Michael Toker, Nitay Calderon et al.
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Mușat
Image Background Serves as Good Proxy for Out-of-distribution Data
Sen Pei
HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning
Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai et al.
Topological Zigzag Spaghetti for Diffusion-based Generation and Prediction on Graphs
Yuzhou Chen, Yulia Gel
Towards Out-of-Modal Generalization without Instance-level Modal Correspondence
Zhuo Huang, Gang Niu, Bo Han et al.
State Representation Learning Using an Unbalanced Atlas
Li Meng, Morten Goodwin, Anis Yazidi et al.
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li, Maoli Liu, Xiangxiang Dai et al.
Procedural Fairness Through Decoupling Objectionable Data Generating Components
Zeyu Tang, Jialu Wang, Yang Liu et al.
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin et al.
ImDy: Human Inverse Dynamics from Imitated Observations
Xinpeng Liu, Junxuan Liang, Zili Lin et al.
Revisiting Mode Connectivity in Neural Networks with Bezier Surface
Jie Ren, Pin-Yu Chen, Ren Wang
Fast Uncovering of Protein Sequence Diversity from Structure
Luca Alessandro Silva, Barthelemy Meynard-Piganeau, Carlo Lucibello et al.
Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising
Zhengwei Yin, Hongjun Wang, Guixu Lin et al.
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Aadirupa Saha, Branislav Kveton
Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
Giuseppe Serra, Florian Buettner
Regretful Decisions under Label Noise
Sujay Nagaraj, Yang Liu, Flavio Calmon et al.
From Search to Sampling: Generative Models for Robust Algorithmic Recourse
Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi
Fengbo: a Clifford Neural Operator pipeline for 3D PDEs in Computational Fluid Dynamics
Alberto Pepe, Mattia Montanari, Joan Lasenby
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging
Behrooz Tahmasebi, Stefanie Jegelka
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
Rui Hu, Yifan Zhang, Zhuoran Li et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Dreamweaver: Learning Compositional World Models from Pixels
Junyeob Baek, Yi-Fu Wu, Gautam Singh et al.
RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
Xi Xie, Yuebo Luo, Hongwu Peng et al.
HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing
Huaijin Wu, Lianqiang Li, Hantao Huang et al.
Uni$^2$Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection
Yubin Wang, Zhikang Zou, Xiaoqing Ye et al.
Machine Unlearning via Simulated Oracle Matching
Kristian G Georgiev, Roy Rinberg, Sam Park et al.
SOHES: Self-supervised Open-world Hierarchical Entity Segmentation
Shengcao Cao, Jiuxiang Gu, Jason Kuen et al.
Conditional Testing based on Localized Conformal $p$-values
Xiaoyang Wu, Lin Lu, Zhaojun Wang et al.
Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula
Youssef Shehata, Benjamin Holzschuh, Nils Thuerey
Improving Neural Optimal Transport via Displacement Interpolation
Jaemoo Choi, Yongxin Chen, Jaewoong Choi
On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
Bokun Wang, Yunwen Lei, Yiming Ying et al.
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Sajad Marvi et al.
BANGS: Game-theoretic Node Selection for Graph Self-Training
Fangxin Wang, Kay Liu, Sourav Medya et al.
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol et al.
Tracking objects that change in appearance with phase synchrony
Sabine Muzellec, Drew Linsley, Alekh Ashok et al.
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Huang et al.
Steering Protein Family Design through Profile Bayesian Flow
Jingjing Gong, Yu Pei, Siyu Long et al.
Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs
Jie Zhang, Zhongqi Wang, Mengqi Lei et al.
Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation
Chenbin Zhang, Zhiqiang Hu, Jiang Chuchu et al.
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel et al.
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Hannah Kniesel, Leon Sick, Tristan Payer et al.
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Tianchi Xie, Jiangning Zhu, Guozu Ma et al.
Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric
Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida et al.
Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
Megh Shukla, Aziz Shameem, Mathieu Salzmann et al.
Transformer Block Coupling and its Correlation with Generalization in LLMs
Murdock Aubry, Haoming Meng, Anton Sugolov et al.
Don't Judge by the Look: Towards Motion Coherent Video Representation
Yitian Zhang, Yue Bai, Huan Wang et al.
AniSDF: Fused-Granularity Neural Surfaces with Anisotropic Encoding for High-Fidelity 3D Reconstruction
Jingnan Gao, Zhuo Chen, Xiaokang Yang et al.
Meta-Continual Learning of Neural Fields
Seungyoon Woo, Junhyeog Yun, Gunhee Kim
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
Zhekai Du, Yinjie Min, Jingjing Li et al.
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
Large (Vision) Language Models are Unsupervised In-Context Learners
Artyom Gadetsky, Andrei Atanov, Yulun Jiang et al.
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
yizhuo Ding, Ke Fan, Yikai Wang et al.
Graph-based Document Structure Analysis
Yufan Chen, Ruiping Liu, Junwei Zheng et al.
Bisimulation Metric for Model Predictive Control
Yutaka Shimizu, Masayoshi Tomizuka
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
Christian Fabian, Kai Cui, Heinz Koeppl
The Complexity of Two-Team Polymatrix Games with Independent Adversaries
Alexandros Hollender, Gilbert Maystre, Sai Ganesh Nagarajan
Conformal Structured Prediction
Botong Zhang, Shuo Li, Osbert Bastani
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam Baddar et al.
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
Bowen Jing, Tommi Jaakkola, Bonnie Berger
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh et al.
Progressive Fourier Neural Representation for Sequential Video Compilation
Haeyong Kang, Jaehong Yoon, DaHyun Kim et al.
Multi-Field Adaptive Retrieval
Millicent Li, Tongfei Chen, Ben Van Durme et al.
Efficient Imitation under Misspecification
Nicolas Espinosa Dice, Sanjiban Choudhury, Wen Sun et al.
Lines of Thought in Large Language Models
Raphaël Sarfati, Toni Liu, Nicolas Boulle et al.
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
Uncovering Latent Memories in Large Language Models
Sunny Duan, Mikail Khona, Abhiram Iyer et al.
ClawMachine: Learning to Fetch Visual Tokens for Referential Comprehension
Tianren Ma, Lingxi Xie, Yunjie Tian et al.
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder
Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi et al.
Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann et al.
ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels
Benjamin Spector, Simran Arora, Aaryan Singhal et al.
LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
Yan Yang, Bin Gao, Ya-xiang Yuan
Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs
Yuheng Zhang, Nan Jiang
Few-shot Hybrid Domain Adaptation of Image Generator
Hengjia Li, Yang Liu, Linxuan Xia et al.
Following the Human Thread in Social Navigation
Luca Scofano, Alessio Sampieri, Tommaso Campari et al.
Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham
From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller et al.
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset, Edouard Duchesnay, Grigis Antoine et al.
Sufficient conditions for offline reactivation in recurrent neural networks
Nanda H Krishna, Colin Bredenberg, Daniel Levenstein et al.
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis et al.
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy et al.
Optimal Brain Apoptosis
Mingyuan Sun, Zheng Fang, Jiaxu Wang et al.
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Jihyo Kim, Seulbi Lee, Sangheum Hwang
DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS
Ilan Price, Nicholas Daultry Ball, Adam Jones et al.
Subtask-Aware Visual Reward Learning from Segmented Demonstrations
Changyeon Kim, Minho Heo, Doohyun Lee et al.
$F^3Set$: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Zhaoyu Liu, Kan Jiang, Murong Ma et al.
Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling
Yuxin Dai, Qi Wang, Jingsen Zhu et al.
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec et al.
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami et al.
Out-Of-Domain Unlabeled Data Improves Generalization
seyed amir hossein saberi, Amir Najafi, Alireza Heidari et al.
Fair Clustering in the Sliding Window Model
Vincent Cohen-Addad, Shaofeng Jiang, Qiaoyuan Yang et al.
Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui LIU et al.
DICE: Data Influence Cascade in Decentralized Learning
Tongtian Zhu, Wenhao Li, Can Wang et al.
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
Rohan Subramani, Marcus Williams, Max Heitmann et al.
Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer
XINYUE HU, Zhibin Duan, Bo Chen et al.
Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
Kai Gan, Bo Ye, Min-Ling Zhang et al.
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers
Yuchen Liang, Peizhong Ju, Yingbin Liang et al.
OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference
Dujian Ding, Bicheng Xu, Laks Lakshmanan
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
Weiqiang He, Hendrik Fichtenberger, Pan Peng
TAU-106K: A New Dataset for Comprehensive Understanding of Traffic Accident
Yixuan Zhou, Long Bai, Sijia Cai et al.
Agent Skill Acquisition for Large Language Models via CycleQD
So Kuroki, Taishi Nakamura, Takuya Akiba et al.
Online Information Acquisition: Hiring Multiple Agents
Federico Cacciamani, Matteo Castiglioni, Nicola Gatti
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier et al.
Representative Guidance: Diffusion Model Sampling with Coherence
Anh-Dung Dinh, Daochang Liu, Chang Xu
Physics-aligned field reconstruction with diffusion bridge
Zeyu Li, Hongkun Dou, Shen Fang et al.
Selective Label Enhancement Learning for Test-Time Adaptation
Yihao Hu, Congyu Qiao, Xin Geng et al.
Structural Inference with Dynamics Encoding and Partial Correlation Coefficients
Aoran Wang, Jun Pang
ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye et al.
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav, Nicholas Monath, Manzil Zaheer et al.
Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities in Biomedicine
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension ability
Yujin Han, Lei Xu, Sirui Chen et al.
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings
Edouard YVINEC, Arnaud Dapogny, Kevin Bailly
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density
Sabine Susstrunk, Mathieu Salzmann, Chen Liu et al.
Optimizing importance weighting in the presence of sub-population shifts
Floris Holstege, Bram Wouters, Noud Giersbergen et al.
Endowing Visual Reprogramming with Adversarial Robustness
Shengjie Zhou, Xin Cheng, Haiyang Xu et al.